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Extended mean field control problems: Stochastic maximum principle and transport perspective

Author(s): Acciaio, B; Backhoff-Veraguas, J; Carmona, Rene

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dc.contributor.authorAcciaio, B-
dc.contributor.authorBackhoff-Veraguas, J-
dc.contributor.authorCarmona, Rene-
dc.date.accessioned2021-10-11T14:17:24Z-
dc.date.available2021-10-11T14:17:24Z-
dc.date.issued2019en_US
dc.identifier.citationAcciaio, B, Backhoff-Veraguas, J, Carmona, R. (2019). Extended mean field control problems: Stochastic maximum principle and transport perspective. SIAM Journal on Control and Optimization, 57 (3666 - 3693. doi:10.1137/18M1196479en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1687q-
dc.description.abstractWe study mean feld stochastic control problems where the cost function and the state dynamics depend upon the joint distribution of the controlled state and the control process. We prove suitable versions of the Pontryagin stochastic maximum principle, both in necessary and in sufcient forms, which extend the known conditions to this general framework. We suggest a variational approach for a weak formulation of these control problems. We show a natural connection between this weak formulation and optimal transport on path space, which inspires a novel discretization scheme.en_US
dc.format.extent3666 - 3693en_US
dc.language.isoen_USen_US
dc.relation.ispartofSIAM Journal on Control and Optimizationen_US
dc.rightsAuthor's manuscripten_US
dc.titleExtended mean field control problems: Stochastic maximum principle and transport perspectiveen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1137/18M1196479-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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